Volume 44 Issue 4
Apr.  2022
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JIN Meixiu, ZHU Shihu, WANG Tong, ZHUANG Feifei. Nondestructive Crack Testing via Infrared Thermal Imaging Using Halogen Lamp Excitation[J]. Infrared Technology , 2022, 44(4): 421-427.
Citation: JIN Meixiu, ZHU Shihu, WANG Tong, ZHUANG Feifei. Nondestructive Crack Testing via Infrared Thermal Imaging Using Halogen Lamp Excitation[J]. Infrared Technology , 2022, 44(4): 421-427.

Nondestructive Crack Testing via Infrared Thermal Imaging Using Halogen Lamp Excitation

  • Received Date: 2021-08-08
  • Rev Recd Date: 2021-11-19
  • Publish Date: 2022-04-20
  • The monitoring of rail safety status is crucial to ensure the safe operation of trains. Aiming at rail crack detection, this study quantitatively compares different crack detection technologies and analyzes the application of infrared thermal imaging technology in rail crack detection. The proposed detection technology comprises three parts: external excitation heating, infrared image acquisition and image processing. Firstly, the common excitation methods are introduced and compared. The application of halogen lamps as excitation sources in crack detection is described in detail. Secondly, a halogen lamp excitation based infrared thermal imaging detection experimental platform is developed. Thirdly, an improved image processing algorithm is proposed to enhance the collected infrared image. Finally, this study discusses the prospects of applying the proposed technology in the future.
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  • [1]
    郭火明, 王文健, 刘腾飞, 等. 重载铁路钢轨损伤行为分析[J]. 中国机械工程, 2014, 25(2): 267-272. doi:  10.3969/j.issn.1004-132X.2014.02.025

    GUO Huoming, WANG Wenjian, LIU Tengfei, et al. Analysis of Damage Behavior of Heavy-haul Railway Rails[J]. China Mechanical Engineering, 2014, 25(2): 267-272. doi:  10.3969/j.issn.1004-132X.2014.02.025
    [2]
    田贵云, 高斌, 高运来, 等. 铁路钢轨缺陷伤损巡检与监测技术综述[J]. 仪器仪表学报, 2016, 37(8): 1763-1780. doi:  10.3969/j.issn.0254-3087.2016.08.008

    TIAN Guiyun, GAO Bin, GAO Yunlai, et al. Review of railway rail defect non-destructive testing and monitoring[J]. Chinese Journal of Scientific Instrument, 2016, 37(8): 1763-1780. doi:  10.3969/j.issn.0254-3087.2016.08.008
    [3]
    Kim G, Seo M K, Kim Y I, et al. Development of phased array ultrasonic system for detecting rail cracks[J]. Sensors and Actuators A Physical, 2020, 311: 112086. doi:  10.1016/j.sna.2020.112086
    [4]
    JIANG Yi, WANG Haitao, CHEN Shuai, et al. Visual quantitative detection of rail surface crack based on laser ultrasonic technology[J]. Optik, 2021, 237: 166732. doi:  10.1016/j.ijleo.2021.166732
    [5]
    李浩然, 高斌, 张喜源, 等. 电磁热多物理耦合成像检测方法研究[J]. 中国测试, 2020, 46(12): 99-104. doi:  10.11857/j.issn.1674-5124.2020090090

    LI Haoran, GAO Bin, ZHANG Xiyuan, Research on imaging detection method of thermo-electromagnetic multi-physical coupling effects[J]. China Measurement & Test, 2020, 46(12): 99-104. doi:  10.11857/j.issn.1674-5124.2020090090
    [6]
    YUAN F, YU Y, LIU B, et al. Investigation on velocity effect in pulsed eddy current technique for detection cracks in ferromagnetic material [C]//IEEE Transactions on Magnetics, 2020, 56(9): 3012341.
    [7]
    杨理践, 耿浩, 高松巍. 基于多级磁化的高速漏磁检测技术研究[J]. 仪器仪表学报, 2018, 39(6): 148-156. https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB201806019.htm

    YANG Lijian, GENG Hao, GAO Songwei. Study on high-speed magnetic flux leakage testing technology based on multistage magnetization[J]. Chinese Journal of Scientific Instrument, 2018, 39(6): 148-156. https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB201806019.htm
    [8]
    XU Changhang, XIE Jing, CHEN Guoming, et al. An infrared thermal image processing framework based on superpixel algorithm to detect cracks on metal surface[J]. Infrared Physics and Technology, 2014, 67: 266-272. doi:  10.1016/j.infrared.2014.08.002
    [9]
    郑凯, 江海军, 陈力. 红外热波无损检测技术的研究现状与进展[J]. 红外技术, 2018, 40(5): 401-411. http://hwjs.nvir.cn/article/id/hwjs201805001

    ZHENG Kai, JIANG Haijun. CHEN Li. Infrared thermography NDT and its development[J]. Infrared Technology, 2018, 40(5): 401-411 http://hwjs.nvir.cn/article/id/hwjs201805001
    [10]
    YUAN L, ZHU X, HONG K. Detection of material surface cracks by infrared non-destructive testing[C]//2020 11th International Conference on Prognostics and System Health Management (PHM-2020 Jinan), 2020: DOI: 10.1109/PHM-Jinan48558.2020.00114.
    [11]
    YANG J, WANG W, LIN G, et al. Infrared thermal imaging-based crack detection using deep learning[J]. IEEE Access, 2019, 7: 182060-182077. doi:  10.1109/ACCESS.2019.2958264
    [12]
    沈功田, 王尊祥. 红外检测技术的研究与发展现状[J]. 无损检测, 2020, 42(4): 1-9, 14. https://www.cnki.com.cn/Article/CJFDTOTAL-WSJC202004003.htm

    SHEN Gongtian, WANG Zunxiang, Progress of infrared testing technology[J]. Nondestructive Testing, 2020, 42(4): 1-9, 14. https://www.cnki.com.cn/Article/CJFDTOTAL-WSJC202004003.htm
    [13]
    徐欢, 殷晨波, 李向东, 等. 超声红外检测中裂纹微观界面生热的数值模拟[J]. 南京工业大学学报: 自然科学版, 2019, 41(4): 493-500 doi:  10.3969/j.issn.1671-7627.2019.04.015

    XU Huan, YIN Chenbo, LI Xiangdong, et al. Numerical simulation of the heat generated by the microcosmic interface of cracks in ultrasonic infrared detection[J]. Journal of Nanjing Tech University: Natural Science Edition, 2019, 41(4): 493-500. doi:  10.3969/j.issn.1671-7627.2019.04.015
    [14]
    CHI Wubu, ZHAO Bo, LIU Tao, et al. Infrared thermal imaging detection of debonding defects in carbon fiber reinforced polymer based on pulsed thermal wave excitation[J]. Thermal Science, 2020, 24(6B): 3887 - 3892.
    [15]
    顾桂梅, 贾文晶. 钢轨轨底裂纹红外热波无损检测数值模拟分析[J]. 红外技术, 2018, 40(3): 294-299. http://hwjs.nvir.cn/article/id/hwjs201803016

    GU Guimei, JIA Wenjing. Numerical simulation analysis of infrared thermal wave nondestructive testing of rail bottom crack[J]. Infrared Technology, 2018, 40(3): 294-299. http://hwjs.nvir.cn/article/id/hwjs201803016
    [16]
    李玉杰, 李科, 钟安彪, 等. 卤素灯加热红外成像检测技术仿真研究[J]. 激光与红外, 2016, 46(12): 1477-1480. doi:  10.3969/j.issn.1001-5078.2016.12.008

    LI Yujie, LI Ke, ZHONG Anbiao, et al. Simulation research of infrared image detection technology for halogen lamp heating[J]. Laser & Infrared, 2016, 46(12): 1477-1480. doi:  10.3969/j.issn.1001-5078.2016.12.008
    [17]
    ZHOU Zhenggan, HE Pengfei, ZHAO Hanxue, et al. Detection of skin desoldering defect in Ti-alloy honeycomb structure using lock-in infrared thermography test[J]. Journal of Beijing University of Aeronautics and Astronautics. 2016, 42(9): 1795-1802. https://www.cnki.com.cn/Article/CJFDTOTAL-BJGD202103011.htm
    [18]
    黄涛. 基于红外热波技术的钢轨疲劳裂纹深度定量检测研究[D]. 兰州: 兰州交通大学, 2015.

    HUANG Tao. Rail Fatigue Crack Depth Quantitative Detection Based on Infrared Thermal Wave Technology[D]. Lanzhou: Lanzhou Jiaotong University, 2015.
    [19]
    李科, 钟安彪, 李玉杰, 等. 基于热风激励的红外成像检测技术研究[J]. 激光与红外, 2016, 46(7): 823-826. doi:  10.3969/j.issn.1001-5078.2016.07.010

    LI Ke, ZHONG Anbiao, LI Yujie. Research on infrared imaging detection based on hot wind heating[J]. Laser & Infrared, 2016, 46(7): 823-826. doi:  10.3969/j.issn.1001-5078.2016.07.010
    [20]
    王加, 周永康, 李泽民, 等. 非制冷红外图像降噪算法综述[J]. 红外技术, 2021, 43(6): 557-565. http://hwjs.nvir.cn/article/id/380dcf6e-de3d-4411-ab70-e246d5c8ea27

    WANG Jia, ZHOU Yongkang, LI Zemin, et al. A survey of uncooled infrared image denoising algorithms[J]. Infrared Technology, 2021, 43(6): 557-565 http://hwjs.nvir.cn/article/id/380dcf6e-de3d-4411-ab70-e246d5c8ea27
    [21]
    王浩, 张叶, 沈宏海, 等. 图像增强算法综述[J]. 中国光学, 2017, 10(4): 438-448. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGA201704005.htm

    WANG Hao, ZHANG Ye, SHEN Honghai, et al. Review of image enhancement algorithms[J]. Chinese Optics, 2017, 10(4): 438-448. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGA201704005.htm
    [22]
    李贤阳, 阳建中, 杨竣辉, 等. 基于改进的直方图均衡化与边缘保持平滑滤波的红外图像增强算法[J]. 计算机应用与软件, 2019, 36(3): 96-103. https://www.cnki.com.cn/Article/CJFDTOTAL-JYRJ201903020.htm

    LI Xianyang, YANG Jianzhong, YANG Junhui, et al. Infrared image enhancement algorithm based on improved histogram equalization and edge preserving smooth filtering[J]. Computer Applications and Software, 2019, 36(3): 96-103. https://www.cnki.com.cn/Article/CJFDTOTAL-JYRJ201903020.htm
    [23]
    陈明, 谭涛. 基于形态学和高斯滤波的图像快速去雾算法[J]. 计算机应用与软件, 2019, 36(12): 209-213. https://www.cnki.com.cn/Article/CJFDTOTAL-JYRJ201912034.htm

    CHEN Ming, TAN Tao. A fast image denoising algorithm based on morphology and Gaussian filter[J]. Computer Applications and Software, 2019, 36(12): 209-213. https://www.cnki.com.cn/Article/CJFDTOTAL-JYRJ201912034.htm
    [24]
    宋人杰, 刘超, 王保军. 一种自适应的Canny边缘检测算法[J]. 南京邮电大学学报: 自然科学版, 2018, 38(3): 72-76. https://www.cnki.com.cn/Article/CJFDTOTAL-NJYD201803012.htm

    SONG Renjie, LIU Chao, WANG Baojun. Adaptive Canny edge detection algorithm[J]. Journal of Nanjing University of Posts and Telecommunications: Natural Science Edition. 2018, 38(3): 72-76. https://www.cnki.com.cn/Article/CJFDTOTAL-NJYD201803012.htm
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